Senior AI Platform Engineer

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Senior AI Platform Engineer based in Netherlands. This is a senior engineering opportunity focused on building the foundational platform layer behind secure, production-grade AI applications. You will design shared infrastructure, services, integrations, and developer tooling that enable teams to build and scale AI capabilities efficiently. The role combines hands-on work with LLMs, AI agents, RAG, tool calling, and AI workflows with strong data engineering and platform engineering practices. You will leverage modern cloud and data technologies to turn experimental AI use cases into reliable, scalable production systems. Working across Engineering, Product, and IT, you will establish technical patterns, reusable capabilities, and governance standards for AI development. This fully remote role is ideal for an experienced engineer who enjoys solving foundational problems and shaping how AI is built and operated across an organization. Design and build reusable platform capabilities supporting LLM applications, AI agents, RAG, tool calling, and AI workflows. Develop scalable data and knowledge pipelines covering ingestion, embeddings, retrieval, vector search, metadata, and knowledge management. Build secure integrations between AI applications, enterprise data, and business systems using APIs, MCP, tool calling, and comparable integration patterns. Develop reusable frameworks, libraries, services, SDKs, and developer tooling that allow engineering teams to build AI applications efficiently. Establish technical standards and patterns for AI deployment, observability, evaluation, monitoring, and lifecycle management. Define and improve approaches for measuring AI quality, accuracy, latency, reliability, security, and cost. Take AI capabilities from experimentation and prototyping through reliable, scalable, and maintainable production deployment. Ensure AI platform capabilities comply with security, privacy, authentication, authorization, access control, and data governance requirements. Work with Engineering, Product, and IT teams to identify AI opportunities and translate ambiguous business needs into practical technical solutions. Evaluate emerging AI models, frameworks, infrastructure technologies, and development approaches to determine their potential business value. Contribute to the evolution of platform architecture, engineering standards, and reusable AI capabilities across the organization. Promote strong data engineering and platform practices around data modeling, data quality, secure data access, and operational reliability. Requirements: 5+ years of professional experience in data engineering, platform engineering, backend engineering, or a closely related discipline, with experience building and operating production systems. Strong proficiency in Python and SQL . Hands-on experience building and deploying production applications or services using LLMs and generative AI . Practical experience with RAG, embeddings, vector search, tool/function calling, AI agents, or enterprise knowledge systems . Strong data engineering fundamentals, including data pipelines, data modeling, data quality, and secure data access. Experience with Snowflake, Databricks, or comparable modern data platforms , together with tools such as dbt, Airflow, or similar technologies. Proven experience building shared AI infrastructure, platforms, or reusable AI capabilities rather than focusing exclusively on individual AI applications. Experience taking AI systems from experimentation and proof of concept through reliable production deployment. Solid understanding of security, authentication and authorization, privacy, access control, and data governance. Strong ability to translate ambiguous AI opportunities into practical, scalable engineering solutions. Excellent communication and collaboration skills, with the abili